Post on 23-Feb-2016
description
Practical Session: Bayesian evolutionary analysis by sampling trees (BEAST)
Rebecca R. Gray, Ph.D.Department of Pathology
University of Florida
• BEAST:– is a cross-platform program for Bayesian MCMC
analysis of molecular sequences– entirely orientated towards rooted, time-measured
phylogenies inferred using strict or relaxed molecular clock models
– can be used as a method of reconstructing phylogenies, but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology
– uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability
Citations• The recommended citation for this program is:
– Drummond AJ, Rambaut A (2007) "BEAST: Bayesian evolutionary analysis by sampling trees." BMC Evolutionary Biology 7:214
• To cite the relaxed clock model in BEAST: – Drummond AJ, Ho SYW, Phillips MJ & Rambaut A (2006)
PLoS Biology 4, e88• To cite the Bayesian Skyline model in BEAST:
– Drummond AJ, Rambaut A & Shapiro B and Pybus OG (2005) Mol Biol Evol 22, 1185-1192
• The original MCMC paper was: – Drummond AJ, Nicholls GK, Rodrigo AG & Solomon W
(2002) Genetics 161, 1307-1320
Basic Pipeline• 1) setting up xml file (beauti)• 2) running xml file (beast)• 3) evaluating the performance of the run
(Tracer)• 4) comparing models, obtaining
estimates of parameters (Tracer)• 5) summarizing the tree distribution
(TreeAnnotator)• 6) viewing MCC tree (Figtree)
Downloading programs• http://beast.bio.ed.ac.uk/Main_Page\
– Download contains beauti, BEAST, TreeAnnotator
• http://beast.bio.ed.ac.uk/Tracer• http://beast.bio.ed.ac.uk/FigTree
PRACTICAL: RIFT VALLEY FEVER VIRUS
Epidemiology of RVF• The virus was first identified in 1931 in the Rift
Valley of Kenya
• Mosquito vector, primarily infects livestock
• 1997–1998, a major outbreak occurred in Kenya, Somalia and the United Republic of Tanzania
• September 2000 cases were confirmed in Saudi Arabia and Yemen (first reported occurrence of the disease outside the African continent)
Setting up xml file in beauti• Requires a nexus file
– Helpful to have dates with the sample name
– Use the finest resolution available• GUI interface allows basic selection
of parameters • Xml file can be manually edited to
test specific hypotheses/tweak run
Beauti practical• Import alignment (g_63.nex)• Tip dates – use tipdates, guess dates (years
since some time in the past)• Site models – use GTR + G, empirical base
frequencies• Test hypothesis of strict vs. relaxed
molecular clock• Trees – coalescent tree prior – constant size• 5 x 107 generations
BEAST
• Open xml file with text editor• Run in beast• Check mixing of the MCMC chain• Open S log files in Tracer• Open L and G2 log files• What can we do about the trace??
Proper mixing• First step – run chain longer
– Open L200 files• Other steps to try:
– Over parameterization – reduce complexity
– Temporal/phylogenetic signal– Priors are inappropriate
Model testing• Bayes factors:
– Compare estimates of the marginal likelihoods of the models of interest
– 2*(ln marginal likelihood model 1 – ln marginal likelihood model 2)
– >10, strong support for alternative (more complex model)
• Strict clock vs. relaxed clock– Also consider the coefficient of variation
Summarizing tree• TreeAnnotator
– Burnin 10% (501 samples)– Keep median heights– MCC tree
• Visualizing tree: FigTree– Posterior probabilities for branches– Median heights for clades of interest
Advanced analyses• Different coalescent priors
– Parametric models (exponential, logistic)– Bayesian skyline plots
• Phylogeography– Lemey et al, 2009, Plos Computational
Biology• Site specific rates of variation
Change in effective population size over time
Log1
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16
Bayesian Genealogy Of G Gene
1916 (1868-1942)
Additional resources• Tutorials on the beast website,
google group• 16th International BioInformatics
Workshop on Virus Evolution and Molecular Epidemiology– Johns Hopkins University, Baltimore– 29 August - 03 September 2010,
Bethesda, USA– http://www.rega.kuleuven.be/cev/
workshop/